Bayesian inversion of synthetic AVO data to assess fluid and shale content in sand-shale media

Abstract

Reservoir characterization of sand-shale sequences has always challenged geoscientists due to the presence of anisotropy in the form of shale lenses or shale layers. Water saturation and volume of shale are among the fundamental reservoir properties of interest for sand-shale intervals, and relate to the amount of fluid content and accumulating potentials of such media. This paper suggests an integrated workflow using synthetic data for the characterization of shaley-sand media based on anisotropic rock physics (T-matrix approximation) and seismic reflectivity modelling. A Bayesian inversion scheme for estimating reservoir parameters from amplitude vs. offset (AVO) data was used to obtain the information about uncertainties as well as their most likely values. The results from our workflow give reliable estimates of water saturation from AVO data at small uncertainties, provided background sand porosity values and isotropic overburden properties are known. For volume of shale, the proposed workflow provides reasonable estimates even when larger uncertainties are present in AVO data.

Prediction of dispersion and attenuation on elastic wave velocities in partially saturated rock based on the fluid distribution obtained from three-dimensional (3D) micro-CT images

“…Characterization of fluid distribution in a reservoir is essential in several scenarios, such as monitoring CO 2 geological storage and gas and oil production exploration (Klimentos, 1995;Tester et al, 2007). Seismic waves are known to be affected by fluid; therefore, it is a valuable tool for detecting in situ fluid properties (Adelinet et al, 2011;Anwer et al, 2017;He et al, 2020). At the mesoscopic scale, for a biphasic saturated rock, like gas and water, seismic waves induce a pore pressure gradient due to the difference in the fluid bulk moduli, causing diffusion between the different fluid phases and, thus, energy transfer (Pride et al, 2004;Wang Y. et al, 2022b).…”

The accuracy of AVA approximations in isotropic media assessed via synthetic numerical experiments: Implications for the determination of porosity

“…Sun et al (2015) introduced pre-stack elastic integration techniques by considering the impact of rock physics and amplitude-preserving processing algorithms on pre-stack inversion. Finally, Anwer et al (2017) utilised an anisotropic T-matrix approach in a Bayesian inversion scheme to characterise anisotropic sand-shale medium.…”